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University of Tennessee, Knoxville

2022

Computational Fluid Dynamics; Adjoint Sensitivities; Optimization; Reduced-order Modeling

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Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky Dec 2022

Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky

Doctoral Dissertations

The adoption of mathematically formal simulation-based optimization approaches within aerodynamic design depends upon a delicate balance of affordability and accessibility. Techniques are needed to accelerate the simulation-based optimization process, but they must remain approachable enough for the implementation time to not eliminate the cost savings or act as a barrier to adoption.

This dissertation introduces a reduced-order model technique for accelerating fixed-point iterative solvers (e.g. such as those employed to solve primal equations, sensitivity equations, design equations, and their combination). The reduced-order model-based acceleration technique collects snapshots of early iteration (pre-convergent) solutions and residuals and then uses them to project …